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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-V3 vs Gemini 2.0 Flash vs Claude Sonnet 3.5 v2

Gemini 2.0 Flash comes out ahead, 65 to 54 and 45 on our weighted score.

  1. DeepSeek

    DeepSeek-V3

    Released Dec 26, 2024

    45/100
    • ECI132.3
    • Price$0.32 / $1.10
    • Context131K
    Full specs Remove DeepSeek-V3
  2. Our pick

    Google

    Gemini 2.0 Flash

    Released Dec 11, 2024

    65/100
    • ECI134.7
    • Price—
    • Context1.05M
    Full specs Remove Gemini 2.0 Flash

  3. Anthropic

    Claude Sonnet 3.5 v2

    Released Oct 22, 2024

    54/100
    • ECI133.5
    • Price$3.00 / $15.00
    • Context200K
    Full specs Remove Claude Sonnet 3.5 v2
01 — Verdict

Gemini 2.0 Flash is our pick

Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and DeepSeek-V3 (45). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityGemini 2.0 FlashCapabilities Index (ECI): Gemini 2.0 Flash 134.7 · Claude Sonnet 3.5 v2 133.5 · DeepSeek-V3 132.3
  • Lowest priceDeepSeek-V3DeepSeek-V3 $0.515 · Claude Sonnet 3.5 v2 $6.00 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
  • Longest contextGemini 2.0 FlashGemini 2.0 Flash 1,048,576 · Claude Sonnet 3.5 v2 200,000 · DeepSeek-V3 131,072 tokens
  • Widest inputsGemini 2.0 FlashDeepSeek-V3: Text · Gemini 2.0 Flash: Text, Images, PDFs, Audio, Video · Claude Sonnet 3.5 v2: Text, Images, PDFs
  • Self-hostingDeepSeek-V3Publishes downloadable weights (DeepSeek Model License)
How the score is built
MeasureWeightDeepSeek-V3Gemini 2.0 FlashClaude Sonnet 3.5 v2
CapabilityCapabilities Index (ECI)67%565957
Inputs & features20%259060
Context window13%246132
Overall100%45/10065/10054/100

Left out because at least one model lacks the data: price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

DeepSeek-V3 vs Gemini 2.0 Flash vs Claude Sonnet 3.5 v2 specifications side by side
SpecificationDeepSeek-V3DeepSeekGemini 2.0 FlashGoogleClaude Sonnet 3.5 v2Anthropic
Capability
Capabilities Index (ECI)132.3134.7 (best)133.5
ECI rank#121 of 148#116 of 148 (best)#119 of 148
GPQA DiamondGraduate-level science questions56.5% (best)—55.3%
OTIS Mock AIME 2024–2025Competition mathematics15.8% (best)—8.5%
Price per million tokens
Input$0.32 (best)—$3.00
Output$1.10 (best)—$15.00
Cached input———
Blended (3:1)$0.515 (best)—$6.00
Long-context rateSame rate—Same rate
Price sourceMedian of 5 providers—Median of 1 providers
Limits
Context window131,072 tokens1,048,576 tokens (best)200,000 tokens
Max output8,192 tokens8,192 tokens8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoYesYes
AudioNoYesNo
VideoNoYesNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenDeepSeek Model LicenseProprietaryProprietary
API model ID———
API providers5 (best)—1
ReleasedDec 26, 2024Dec 11, 2024Oct 22, 2024
Knowledge cutoff—Jun 2024Apr 30, 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • DeepSeek-V3$5.40
  • Gemini 2.0 Flash—
  • Claude Sonnet 3.5 v2$60.00
04 — Questions

Which should you choose?

Which is better: DeepSeek-V3, Gemini 2.0 Flash or Claude Sonnet 3.5 v2?

Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against Claude Sonnet 3.5 v2 (54) and DeepSeek-V3 (45). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, DeepSeek-V3, Gemini 2.0 Flash or Claude Sonnet 3.5 v2?

DeepSeek-V3 is cheaper at $0.32 input / $1.10 output per million tokens (median across 5 API providers). Claude Sonnet 3.5 v2 costs $3.00 input / $15.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.515 per million tokens for DeepSeek-V3 versus $6.00 for Claude Sonnet 3.5 v2 (12× as much). Gemini 2.0 Flash has no published per-token price.

Which scores higher on benchmarks?

Gemini 2.0 Flash scores higher on the Capabilities Index (ECI): Gemini 2.0 Flash 134.7 (#116 of 148), Claude Sonnet 3.5 v2 133.5 (#119 of 148) and DeepSeek-V3 132.3 (#121 of 148). The confidence ranges of the top two overlap (124.3–136.7 vs 129.2–137.5), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-V3, Gemini 2.0 Flash and Claude Sonnet 3.5 v2 yet, so there is no like-for-like coding score. On overall capability, Gemini 2.0 Flash leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Gemini 2.0 Flash has the largest context window at 1,048,576 tokens, against 200,000 for Claude Sonnet 3.5 v2 and 131,072 for DeepSeek-V3. Maximum output per response: DeepSeek-V3 up to 8,192, Gemini 2.0 Flash up to 8,192, Claude Sonnet 3.5 v2 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-V3 accepts text; Gemini 2.0 Flash accepts text, images, PDFs, audio and video; Claude Sonnet 3.5 v2 accepts text, images and PDFs. Gemini 2.0 Flash handles the widest range of inputs.

Are any of these open source?

DeepSeek-V3 publishes its weights (DeepSeek Model License) and can be self-hosted; Gemini 2.0 Flash and Claude Sonnet 3.5 v2 is proprietary.

Which is newer?

DeepSeek-V3 is the newest, released Dec 26, 2024. Gemini 2.0 Flash came out Dec 11, 2024; Claude Sonnet 3.5 v2 came out Oct 22, 2024. Knowledge cutoff: Gemini 2.0 Flash Jun 2024, Claude Sonnet 3.5 v2 Apr 30, 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.

05 — Keep comparing

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